computer-vision
Non-exemplar-based Class Incremental Learning
3260 papers • 126 benchmarks • 313 datasets
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Benchmarks
These leaderboards are used to track progress in non-exemplar-based-class-incremental-learning
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cifar100
cifar100
TinyImageNet
TinyImageNet
ImageNetSubset
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Most implemented papers
NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization for Continual Learning
T. Malepathirana, Damith A. Senanayake, Saman K. Halgamuge•Thu Aug 17 2023
NAPA-VQ: Neighborhood Aware Prototype Augmentation with Vector Quantization, a framework that reduces class overlap in NECIL, and outperforms the State-of-the-art NECIL methods by an average improvement of 5%, 2%, and 4% in accuracy and 10%, 3%, and 9% in forgetting respectively.
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